Substrate Topography Determines Neuronal Polarizationand Growth In VitroLiesbeth Micholt1,2, Annette Gartner3*, Dimiter Prodanov1,5, Dries Braeken1*, Carlos G. Dotti3,4*,
Carmen Bartic1,2
1 Life Science Technologies, Imec, Leuven, Belgium, 2 Solid State Physics and Magnetism Section, University of Leuven, Leuven, Belgium, 3VIB Center for the Biology of
Disease, Leuven, and Center for Human Genetics, University of Leuven, Leuven, Belgium, 4Centro de Biologıa Molecular ‘‘Severo Ochoa’’, CSIC/UAM, Madrid, Spain,
5 Environment Health and Safety, Imec, Leuven, Belgium
Abstract
The establishment of neuronal connectivity depends on the correct initial polarization of the young neurons. In vivo,developing neurons sense a multitude of inputs and a great number of molecules are described that affect their outgrowth.In vitro, many studies have shown the possibility to influence neuronal morphology and growth by biophysical, i.e.topographic, signaling. In this work we have taken this approach one step further and investigated the impact of substratetopography in the very early differentiation stages of developing neurons, i.e. when the cell is still at the round stage andwhen the first neurite is forming. For this purpose we fabricated micron sized pillar structures with highly reproduciblefeature sizes, and analyzed neurons on the interface of flat and topographic surfaces. We found that topographic signalingwas able to attract the polarization markers of mouse embryonic neurons -N-cadherin, Golgi-centrosome complex and thefirst bud were oriented towards topographic stimuli. Consecutively, the axon was also preferentially extending along thepillars. These events seemed to occur regardless of pillar dimensions in the range we examined. However, we founddifferences in neurite length that depended on pillar dimensions. This study is one of the first to describe in detail the veryearly response of hippocampal neurons to topographic stimuli.
Citation: Micholt L, Gartner A, Prodanov D, Braeken D, Dotti CG, et al. (2013) Substrate Topography Determines Neuronal Polarization and Growth In Vitro. PLoSONE 8(6): e66170. doi:10.1371/journal.pone.0066170
Editor: Alexandre Hiroaki Kihara, Universidade Federal do ABC, Brazil
Received January 15, 2013; Accepted May 3, 2013; Published June 13, 2013
Copyright: � 2013 Micholt et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Part of this work was supported by the Flanders Fund for Scientific Research (FWO G 0.666.10N, www.fwo.be), the Federal Office for Scientific Affairs(IUAP p6/43), Flemish Government Methusalem Grant and Spanish Ministry of Science and Innovation Ingenio-Consolider CSD2010-00064 and SAF2010-14906(CGD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors want to declare that the authors affiliated with Imec, which is a nonprofit research institute with no commercial activities,have no further competing interests. Thus, this affiliation does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.
* E-mail: [email protected] (CGD); [email protected] (DB); [email protected] (AG)
Introduction
In vitro, neuronal polarization –i.e. the transition from a newly
born round cell to an electrically active and fully interconnected
adult neuron- takes place in five distinct steps. In stage 1 -shortly
after plating- several thin filopodia are formed. Some hours later
several minor processes -immature neurites- are generated during
stage 2. In stage 3, 12h post plating, one neurite rapidly extends
to form the axon, and all the neurites mature over the next week
during stage 4. Finally dendrites and axon become synaptically
functional in stage 5 [1,2]. The fact that polarization occurs in
the homogenous environment of the tissue culture dish has led to
the notion that this is an autonomous, intrinsic, process [3,4].
Recent work revealed that one such mechanism is the presence
of an N-cadherin cluster in one pole of the cell in the
immediately post-mitotic neuron, from which a first neurite
subsequently emerges [5,6]. The first neurite afterwards becomes
the axon [2,7]. In agreement with an essential role of the N-
cadherin crescent in cell polarization, the ectopic exposure to
exogenous N-cadherin was shown sufficient to favor the
formation of the first bud at the new site [5]. This last result
indicates that, despite their intrinsic predisposition to polarize at
a given place (i.e. the pole with clustered N-cadherin), a newborn
neuron has the nominal capacity to allow neurite formation
everywhere in the sphere. This possibility could be of great value
in nerve regeneration scenarios.
Numerous in vitro studies have shown that different types of
structured surfaces can have a strong influence on neuronal
growth and morphology [8–11]. This is also true in vivo, where
cells are not only influenced by chemical signaling but also by
topographic structures, as they provide mechanical support and
guidance for growth and differentiation. Examples of in vivo
guiding topography are the already formed glial processes and pre-
existing axons, along which new axons migrate to establish
connectivity [12–15]. Many studies have sought to explain how
cellular and, more specifically, neuronal morphology are deter-
mined by topography [10,16–19]. An important observation was
that neurons sense isotropic micro-fabricated pillar surfaces, since
they align to the pillar geometry. This can be explained by the
tendency of neurites to follow existing contacts, but if a new
contact -i.e. pillar- is nearby, they extend to contact the new
location resulting in highly aligned and branched neuronal arbors
[8,11,20]. All of these studies focused on neurons in stage 3 and
further, when axon and dendrite identities were already defined.
The study of the role of topography in relation to the generation of
the first neurite is highly relevant since the position of the first
neurite defines the axis of migration of neurons, and this is
important for the proper organization of the brain [5–7].
PLOS ONE | www.plosone.org 1 June 2013 | Volume 8 | Issue 6 | e66170
In recent years different microstructures have been used to
influence neuronal growth and behavior. In general, these used
either anisotropic [19,21] – e.g. fibers and grooves- and isotropic
[8,22] – e.g. pillars, holes and nanorough surfaces- topographic
stimuli. All of them have been shown to affect neuronal
morphology. However, whether any of these has a more
pronounced effect on axonal development and growth than others
is not clear. When neurons are plated on grooved substrates they
can either align according to the direction of the groove (‘contact
guidance’) or orient perpendicular to the grooves, generally
referred to as ‘perpendicular contact guidance’ [19]. With the
use of interrupted microstructures (holes/pillars) this type of
contact guidance is more readily realized [10,11]. In a recent
publication Fozdar et al. [16] compared different shapes (lines and
holes of (i) 300 nm and (i) 2 mm) for their ability to attract axons.
The results show that for both dimension sizes, holes –or in
general, interrupted features- are a more potent topographic cue
to attract axonal specification, with over 70% of neurons
extending to the holes vs grooves. Also in vivo the existence of
‘guidepost’ cells, which are specific cells located at discrete
locations during embryonic development that serve as ‘stepping
stones’ during axon pathfinding, is described in literature and has
been shown in invertebrates [11,23] and it has been suggested that
this mechanism is conserved throughout vertebrates and perhaps
even mammals [24].
In this work we investigated how neurons polarize in response to
topographic stimuli and how this affects the outgrowth behavior.
To this end we microfabricated surfaces having particular, highly
reproducible, topographic features, and demonstrated their ability
to influence the early phases of neuronal polarization, notably the
formation of the first neurite, axonal differentiation and growth.
Results
Substrate LayoutThe substrates used for the cell cultures were diced from silicon
wafers and consisted of different areas decorated with pillars
having different diameters (1, 1.2, 1.4, 1.6, 1.8, 2, 2.4, 2.8, 4,
5.6 mm), different spacings between pillars (0.6, 0.8, 1, 1.2, 1.4,
1.6, 1.8, 2.0, 2.4, 3.2, 4, 5, 7, 10, 15 mm) and a height of 3 mm(Fig. 1A). In this way a matrix of different pillar configurations was
created on a single support. Scanning electron microscopy images
of areas with different pillar dimensions are shown in Fig. 1B.
Between beds of pillars with different diameters, there is a flat
border area (Fig. 1A, vertical direction). Cells that attached to the
interface between the pillar array and the flat area could thus sense
both the flat and the pillar-decorated surface and were important
for our analysis. The substrates were coated with poly-L-lysine
(PLL) before plating primary hippocampal neurons.
To assess the response to various pillar configurations, we
analyzed the polarity parameters of freshly dissociated primary
hippocampal neurons that settled at the border between the flat
substrate and pillars. Before plating, neurons were kept in
suspension for 2 hours to allow for the regeneration of surface
molecules that may have been destroyed during the trypsin
treatment used for the cell dissociation.
Effect of Pillar Contact on First Sprout and Golgi PositionFirstly, we assessed the effect of the topography on the initial
outgrowth of stage 1 neurons. Since filamentous actin is very
dynamic in the initial stages of neuronal polarization in the
outgrowing neurites, we performed time lapse imaging using the
F-actin probe GFP-UtrCH (Calponin Homology domain of
Utrophin) [25,26]. These experiments revealed that the presence
of a topographic signal determined the position of the first sprout
similar to the situation illustrated in Fig. 2A, where even two
sprouts simultaneously appeared on the ‘‘pillar-side’’ of the cell.
We quantified the first bud distribution with respect to the pillar
contact, taking into account cells with one extension (or multiple
extensions that were all facing the pillars). The topographic
features were grouped according to pillar spacing in dense (0.6–
1 mm), intermediate (1.2–2 mm) and sparse (2.4–7 mm). Fig. 2B
shows that the first sprout was preferentially located on the pillar-
containing region, regardless of the inter-pillar spacing
(96.863.2%, 94.665.4% and 83.3616.7% for a spacing range
of 0.6–1 mm, 1.2–2 mm and 2.4–7 mm, respectively).
Next, we analyzed whether the intracellular polarization of the
Golgi apparatus was also influenced by the pillar proximity. For
this, neurons with multiple minor neurites were also taken into
account. The Golgi-centrosome complex is generally highly co-
localized with the first neurite and the axon, and was therefore
taken here as a simple indicator of neuronal polarization [7,27,28].
For quantification, the Golgi apparatus position was registered as
being ON, when located towards the pillar topography, OFF
when oriented towards the flat. In the current experimental set-up,
the Golgi-centrosome complex position was enriched at the side of
pillar contacts (Fig. 2C). Similar to what has been described in
other experimental conditions [28–30], the Golgi-centrosome
complex position was also found here to be at the base of the first
neurite. Even at this very early stage (2–4 hours in culture) in
about 67% of all cases, the Golgi-centrosome was oriented towards
the pillar contacts for inter-pillar spacings between 0.6 and 2 mm(69.866.3%, 64.266.6% and 67.467.1% for a spacing range of
0.6–1 mm, 1.2–2 mm and 2.4–7 mm, respectively). These experi-
ments show that topographic cues are robust inductors of neuronal
polarization.
Effect of Pillar Contact on N-cadherin CrescentRecently, it has been described that in hippocampal neurons
the Golgi-centrosome complex positioning is preceded by an N-
cadherin crescent located at the pole of the cell from which the
first neurite emerges [5]. This same sequence of events has also
been observed in sensory neurons in Drosophila, where an
initial N-cadherin landmark was followed by the recruitment of
the centrosome [6]. We investigated whether pillar–induced
polarization works via the endogenous pathway, triggering the
accumulation of extracellular N-cadherin or whether an
alternative route is preferred. To distinguish between these
possibilities, we plated neurons onto the substrates for 1h in
presence of a cell tracker (5-Chloromethylfluorescein Diacetate,
CMFDA, Invitrogen). Then, we fixed the neurons and
determined the position of the N-cadherin pole. In this analysis,
cells positioned on the edge of a pillar bed were selected and
grouped as following: (1) soma covering one or more pillars
(Fig. 3A); (2) soma touching the pillars (Fig. 3B). Binning
according to spacing was done in the same way as previously
(dense (0.6–1 mm), intermediate (1.2–2 mm) and sparse (2.4–
7 mm)). The center of the N-cadherin crescent was registered as
ON when being oriented towards the pillars and OFF when
away from the pillars. For a fraction of the total population (for
soma covering and 0.6–1 mm: 8.9%, 1.2–2 mm: 5.7%, 2.4–
7 mm: 5.6%. For soma touching and 0.6–1 mm: 6.8%, 1.2–
2 mm: 7.9%, 2.4–7 mm: 9.2%) it was not possible to classify the
N-cadherin crescent as ON or OFF because they were not
sufficiently polarized yet, these cells were not taken into
account.
From this analysis we found that the N-cadherin crescent was
positioned more frequently at the side of the pillar-structured
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 2 June 2013 | Volume 8 | Issue 6 | e66170
surface when the soma was covering at least one pillar (Fig. 3A,
0.6–1 mm: 65.264.5%, for 1.2–2 mm: 67.864.4%, for 2.4–7 mm:
67.265.7%, p,0.05 for all conditions). Under the condition that
the soma only touched the pillars this trend was less evident
(Fig. 3B, 0.6–1 mm: 60.365.9%, for 1.2–2 mm: 70.766.0%, for
2.4–7 mm: 58.764.7%. For 0.6–1 mm and 2.4–7 mm p,0.1, for
1.2–2 mm p,0.05) but still present.
Axon Growth Preference for Neurons in Contact withPillarsNext, we investigated whether the polarity initially induced by
the topographical cues led to the axon growth preference. For this
purpose, we investigated whether axonal growth was preferentially
taking place on the pillar-structured surface when cells were
sensing this surface (examples are shown in Fig. 4A). The results
showed that a wide range of pillar spacings was able to attract the
axon when the cell soma was contacting or covering the
topography (Fig. 4B). For inter-pillar spacings below 2 mm, the
axons were always located on the pillar bed.
We measured the position of the Golgi apparatus and quantified
whether it was located at the base of the axon (Fig. 4C), as
described previously [2,7,28]. The axis of the cell was first
determined as indicated by the dotted line in Fig. 4A, after which
the location of the Golgi with respect to the axon was determined.
This analysis confirms that the Golgi apparatus was positioned at
the base of the axon after 1 DIV.
Figure 1. Substrate Lay-out. (A) The substrate consisted of individual areas decorated with pillars of different dimensions. The pillar width rangedfrom 1–5.6 mm (1, 1.2, 1.4, 1.6, 1.8, 2, 2.4, 2.8, 4, 5.6 mm) in the vertical direction, while the spacing ranged from 0.6–15 mm (0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8,2.0, 2.4, 3.2, 4, 5, 7, 10, 15 mm) and the height was kept constant at 3 mm. (B) Scanning electron microscopy images of different width and spacing ofpillars. Left is W= 1 mm, S = 1 mm, middle is W= 1.6 mm, S = 1.6 mm, right is W= 5.6 mm, S = 10 mm. Scale bars are 10 mm.doi:10.1371/journal.pone.0066170.g001
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 3 June 2013 | Volume 8 | Issue 6 | e66170
Effect of Pillar Dimensions on Neurite LengthTo understand the relevance of quantitative variation in
topographical cues (i.e. pillar diameter and spacing), neurons
seeded on substrates decorated with different pillar sizes were
analyzed per individual pillar bed. Neuronal architecture was
identified using a neuron specific bIII-tubulin antibody (tuj-1) and
neurite lengths at different time points and on different pillar
parameters were analyzed by semi-automated image analysis
(Metamorph, Molecular devices, see Materials and Methods
section and Fig. S1 for detailed explanation). The longest process,
i.e. the axon, and the average neurite length were significantly
longer compared to cells growing on a flat surface, and this already
after 4h in culture (Fig. 5A, examples shown in Fig. 5B). This
difference in length increased up to about two times on certain
pillar dimensions after 30h in culture (axon length on W=1.6 mm,
S= 1.8 mm is 112.6612.4 mm vs 49.363.2 mm on flat surface,
average process length on W=1.6 mm, S=1.8 mm is
32.363.4 mm vs 17.361.2 mm on flat surface). Examples of
neuronal morphology after 4 and 20 hours for different pillar
parameters are shown in Fig. 5B. Comparing axon length for
different pillar dimensions suggested that there was a range of
optimal width and spacing over the whole substrate, i.e. between 1
and 2 mm for both width and spacing (Fig. 5C) that was able to
generate the longest neurite lengths after 30 h in culture. Time
lapse analysis of hippocampal neurons expressing a GFP-UtrCH
after 1 DIV (Fig. 5D, Movie S1) showed that the actin cytoskeleton
was located close to the pillars, F-actin patches were stabilized at
pillar contacts.
Effect of Pillar Dimensions on Growth Cone AreaIn order to gain insight into the mechanisms by which pillar
contacts enhance growth, we analyzed growth cone morphology.
Previous studies showed that growth cones guided by 2 mm wide
adhesive tracks [31], micron sized pillars [8] and ridges [32] had a
more confined morphology. Fig. 6A shows that the average growth
cone size on a pillar spacing between 0.6–2 mm was significantly
smaller than on a wider pillar spacing of 2.4–5 mm and on flat
surfaces (Student’s t-test, p,0.05 comparing S= 0.6–2 mm vs flat
Figure 2. Analysis of first bud and Golgi-centrosome complex position. (A) Time lapse of neurons expressing the F-actin probe GFP-UtrCH,located on the edge of a pillar bed. Scale bar is 10 mm. (B) Analysis of the first sprout positioned towards (ON) or away (OFF) from the pillars. Dashedline indicates the 50% level. Examples of cells with first sprout ON are shown at the right (C) Analysis of the Golgi positioned towards (ON) or away(OFF) from the pillars. Examples of cells with Golgi ON are shown at the right. Scale bars are 10 mm. *, significantly different from random using X2 test(p,0.05). Blue, Nuclei (Hoechst), Green, Golgi apparatus (GPP130), red, microtubules (tuj-1), grey, substrate. For (B), 0.6–1 n= 31, 1.2–2 n= 37, 2.4–7n= 18. For (C), 0.6–1 n= 53, 1.2–2 n= 53, 2.4–7 n= 43.doi:10.1371/journal.pone.0066170.g002
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 4 June 2013 | Volume 8 | Issue 6 | e66170
and S= 0.6–2 mm vs S= 2.4–7 mm). Growth cone sizes on a
spacing of 2.4–5 mm and on a flat surface were of a similar
magnitude (Fig. 6B). Time lapse analysis (Fig. 6A) showed that the
morphology was stable and that what we observed was not a
transient state. Thus, inter-pillar spaces below 2 mm reduce the
spread of the growth cone. This correlated well with the dimension
range of inter-pillar spacings that lead to faster axonal growth.
Effect of Pillar Dimensions on Tyrosine PhosphorylationPositionsTyrosine phosphorylation is considered as one of the key steps
in signal transduction and regulation of enzymatic activity and is
required in a wide range of signaling pathways such as integrin
signaling and focal adhesion kinase mediated actin nucleation [33–
35]. Hence, we investigated the relationship between this
biochemical modification and pillar-induced growth.
We analyzed the co-localization of phosphotyrosine (PY)
patches with pillars contact points (Fig. 7A). PY patches were
attracted by contact with pillars for the spacing range between 1.2
and 2.0 mm, while this was not the case for spacings below 1.2 mm(e.g. 0.6 mm) and above 2 mm (e.g. 3.2 and 5 mm, Fig.7B).We
established this result by estimating the distribution of the
distances between a PY patch to the closest pillar contact (i.e.
the micro-pillar underlying the neurite). This distribution was
compared against the case were the PY patches were randomly
distributed along the neurites’ length. Briefly, disks having the
same mean area as the average PY patch were randomly placed
inside the neurites projections in a number of independent Monte
Carlo simulations and the nearest point-to-event-distance distri-
bution was calculated. Detailed explanation of image processing
and spatial analysis methods can be found in the Materials and
Methods section and supplementary material (Fig. S2, S3). This
approach was repeated for at least 11 images per pillars pacing
Figure 3. Effect of pillar contact on N-cadherin distribution. (A) Example of a neuron with the soma covering at least one pillar at 1 hour inculture, immunostained for N-cadherin (GC-4). Its N-cadherin crescent is oriented towards the pillar contacts. For 0.6–1 n= 112, 1.2–2 n= 115, 2.4–7n= 67. (B) Example of a neuron with the soma touching the pillars 1 hour in culture. The N-cadherin crescent is in the process of being recruitedtowards the pillar contact.*, significantly different from random (dashed line, 50% for random positioning) using X2-test (p,0.05), # indicatesp,0.1.For 0.6–1 n= 68, 1.2–2 n= 58, 2.4–7 n= 109. Green: CMFDA Cell tracker, Blue: Hoechst. Scale bars are 5 mm.doi:10.1371/journal.pone.0066170.g003
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 5 June 2013 | Volume 8 | Issue 6 | e66170
and the confidence intervals of the distributions were computed
(gray shaded area in Fig. 7B). An overview of the mean observed
patch to pillar distance can be found in Table 1 (individual cases
are given in Table S1). If the measured distance to the pillars
center would be larger than the confidence interval of simulated
distributions, this would indicate that the patches were repelled by
pillar contact. On the other hand, if the measured distance to the
pillar center would be smaller than the confidence interval, the PY
patches would be attracted by pillar contact. The red markers in
Fig. 7B indicate the measured average patch distance to pillar
center. The data shows that for a pillar spacing of 0.6, 3.2 or 5 mm
the mean measured distance from the PY patch to the pillar center
fell within the 95% confidence interval of the simulations and
hence was considered not significantly different. However, for 1.2
and 2 mm pillar spacing the patches were on average closer to the
pillars than expected from the simulated cases. This indicates that
particularly for the spacing range of 1–2 mm, precisely positioned
growth signaling was taking place close to pillar contacts.
F-actin showed a similar aggregation at pillar compared to PY
patches, suggesting that tyrosine phosphorylation is involved in the
regulation of actin remodeling (Fig. 7C). Expression of the GFP-
tagged adaptor protein paxillin-GFP revealed that focal adhesion
Figure 4. Axon position for neurons sensing topography. (A) Examples of axon position for neuronal soma touching the pillars (left) andcovering at leat one pillar (right) (green: tau-1 axon specific staining, red: MAP-2 dendrite specific staining, blue: Hoechst). (B) Axon position analysisfor both touching and covering conditions. (C) Golgi position analysis for both touching and covering conditions (dashed line, 25% for randompositioning).*, significantly different from random. For ‘soma on interface’, 0.6–1 n= 16, 1.2–2 n= 32, 2.4–7 n= 23. For ‘soma touching’, 0.6–1 n= 16,1.2–2 n= 41, 2.4–7 n= 28.doi:10.1371/journal.pone.0066170.g004
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 6 June 2013 | Volume 8 | Issue 6 | e66170
signaling and recruitment were also strongest at pillar contacts
(Fig. 7D) [35–38]. Paxillin has recently been shown to integrate
physical and chemical motility signals by determining the positions
in the cell from where motile processes will form [38].
Discussion
We report that topographic signals determine neuronal
polarization from the very instant that the initial contact with
the physical surface is established. First, we have shown that N-
cadherin is enriched at the site of pillar contact (Fig. 3) even before
the generation of the first bud (Fig. 2). From previous studies it is
known that N-cadherin marks the area of initial neurite formation
[5,6]. And indeed in our experiments we also see, at a high degree
of fidelity, that this initial sprout formation can be generated at the
pillar contacts (Fig. 3) suggesting a conserved cellular response in
reaction to external cues, both chemical and topographic. The
pillar induced sprout formation behavior may well be caused by a
local membrane deformation initiated by mechanical strain, which
activates one or more signaling cascades [39–41].
Our experimental data (Fig. 2–4) showed that the N-cadherin
crescent is positioned at the side of the pillar-structured surface
already in round neurons. We know from previous data that N-
cadherin polarizes spontaneously in neurons which are not in
contact with asymmetric cues [5], and that extrinsically applied N-
cadherin can position this cellular N-cadherin crescent and thus
define the site from which the first neurite, i.e. the future axon,
grows out [5]. However, the mechanism by which the N-cadherin
crescent polarizes towards the pillars is yet unknown. We can
hypothesize that either F-actin, which is concentrated at the pillar
contacts (Fig. 2A, [42,43]) or the accumulation or re-localization of
focal adhesions and receptors triggered by mechanical forces
[11,21,44–46] could attract N-cadherin clustering at the pillar
side.
In any case, we can propose the following model in Fig. 8A,
derived from observations of neurite formation and determination
Figure 5. Analysis of neurite length on different pillar parameters. (A) Axon and average neurite length at different time points after plating.The black line shows the growth evolution on a flat substrate, red shows W=4 mm, S = 2 mm, blue shows W=1.8 mm, S = 1.6 mm. The process lengthsfor W= 1.8 mm, S = 1.6 mm, and W=4 mm, S = 2 mm are significantly (p,0.05) higher than on flat after 4, 8, 12 and 20 h. (B) Examples of neuronalmorphology on flat and on the previously summed pillar parameters. Scale bars are 10 mm. (C) Surface plot of axon length in function of width andspacing after 20 h. Maximal axon length at 20 h is achieved by pillars of W= 1–2 mm and S=1–2 mm. (D) Time lapse imaging (GFP-UtrCH) of a minorneurite extending its processes. See Movie S1 for full time lapse. W=2.8 mm, S = 1.6 mm. Scale bar is 10 mm.doi:10.1371/journal.pone.0066170.g005
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 7 June 2013 | Volume 8 | Issue 6 | e66170
and comprising five distinct steps: when a morphologically round
neuron makes contact with a pillar bed (step 1), N-cadherin (step 2)
and the first bud are recruited towards the pillar contact (step 3).
The Golgi apparatus and centrosome orient at the base of this
neurite (step 4), and the axon arises in turn from the initial sprout
(step 5). For the definition of the polarity axis and axonal identity,
the pillar size and spacing dimensions are seemingly less critical, at
least for the parameters used in this work. However, these
parameters are more significant during axonal outgrowth. The
difference in dimension-dependence of polarization and growth
indicates that those events are not necessarily influenced in the
same way.
During outgrowth, the pillars allow for strong and stable
adhesion locations, through which neurites can exert forces, and at
Figure 6. Growth cone morphology on different substrates. (A) Examples of time lapses of growth cones on pillar beds with differentparameters. The growth cone morphology is stable over longer time (here: 800 s), confirmed by the outlined overlay images. The locations of thepillars are outlined. Scale bar is 5 mm. (B) Average growth cone area on different pillar spacings (Student t-test, p,0.05).doi:10.1371/journal.pone.0066170.g006
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 8 June 2013 | Volume 8 | Issue 6 | e66170
Figure 7. Signaling events at pillar contacts. (A) Example of a hippocampal neuron grown on a pillar substrate (W= 1.6 mm, S = 1.2 mm) stainedfor phosphotyrosine (PY, green) and tuj-1 (red). Scale bar is 5 mm. (B) Comparison of the mean patch distance from the pillar center (red marks) to theconfidence interval for the simulated patches (gray shaded area). For a constant W=1.6 mm, the PY patches are outside of the confidence interval forS = 1.2 mm and S= 2 mm. This is indicated by a *. See Table 1 for detailed parameter values. Individual cases are tabulated in Table S1. The y-axis
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 9 June 2013 | Volume 8 | Issue 6 | e66170
the same time these physical structures act as geometrical
constraints providing directional guidance. The mechanical strain
responsible for the initiation of the first bud enforces this sprout
later on to differentiate into the axon. This occurs with a high
degree of repeatability (Fig. 4).
We observed that axons grow in straight lines (Fig. 4A), similar
to what has been described in the literature [41]. On our substrate
straight paths are obtained by neurites growing in between pillars.
The fact that some pillar dimensions (W=1–2 mm and S= 1–
2 mm) are more favorable for neurite extension (Fig. 5A–C) points
towards a preferred distribution of the growth stimuli, localized at
certain discrete locations. A similar dimension range has been used
in other studies, not only for pillar topographies but also for
grooves and ridges [8,17,32]. The correlation between growth
cone size and outgrowth speed was described also in other neuron
types [31,32]. Growth cone filopodia sensing the environment
rapidly encounter pillars that serve as anchoring points, reducing
the need for a wide fan shaped growth cone. Moreover, this is
likely to reduce the number of protrusion-retraction events, thus
ensuring more robust neurite outgrowth compared to outgrowth
on a flat substrate.
Pillar-axon contacts are enriched in highly dynamic F-actin
clusters (Movie S1). In those clusters we also found an enrichment
of phosphotyrosinated proteins indicating areas of high activity for
growth signaling. Hence, signaling from closely spaced pillars may
lead to a ‘domino’mechanism for growth stimulation, introducing
boosts at pillar contacts and maintaining growth rate constant
compared to the situation of more separated pillars, where
signaling decay occurs (schematic model shown in Fig. 8B).
Hoffman-Kim et al. [11] also suggested that during the process of
axonal pathfinding, axons can respond to a local cue with a
structural change before heading for the next permissive cue (e.g.
pillar).On the other hand, as shown in Table 1, the overall density
of the PY patches is not significantly different for various pillar
spacing ranges, therefore the patch location seems to be of greater
importance rather than the amount of patches present per neurite
area. This is confirmed by Jang et al. (2010) in a previous study
where cells were plated on ridges and were found to not contain a
higher PY content than on a flat surface [32].
A major advantage of our approach of studying neuronal
polarization and growth is the high reproducibility with which the
substrates can be fabricated. The systematic variation of pillar
parameters allows for studying changes in neuronal morphology
occurring as a consequence of pillar contact. In the future
topographically active surfaces can be made ‘smarter’ by
introducing more electrical functionality. In addition to creating
a well-organized neuronal network, this approach also allows for
neuronal stimulation and electrical measurement of signals arising
from single cells in a structured network with a high resolution
[47,48]. Apart from in vitro applications, understanding of the
interface between individual neurons and topographical cues can
have an impact in neuronal repair strategies [11].
To further study which molecular pathways are involved in the
cytoskeletal remodeling in the response to substrate topography,
the precise target proteins with tyrosine phosphorylation sites need
to be identified. A myriad of tyrosine residues are phosphorylated
during signaling. This is the case for e.g. paxillin [34,49], for the
actin nucleation-promoting factor N-WASP [33], and for different
sites of focal adhesion kinase phosphorylated by Src [49]. These
processes can also work in concert, initiated by mechanical tension
that activates for instance mechanosensitive ion channels by the
force neurites are exerting on the pillars while elongating [40].
Plenty of work remains to be done in order to unravel the
contribution of each of these possible pathways. Since we observed
that paxillin has a similar patch pattern than phosphotyrosine
(Fig. 7A), we can assume that at least phosphorylation of paxillin is
one of the pathways followed in signal transduction response the
purely topographical input. Another unanswered question is which
receptor or sensing mechanism is located upstream from the
phosphorylation of tyrosine. The most likely candidate is integrin
that has been shown to be mechanosensitive, a property shared
with mechanosensitive ion channels and G protein-coupled
receptors [11,50]. It is interesting to note that integrin signaling
is possible even without any localized ECM ligand to bind to, since
we coated only with poly-L-lysine. It has been shown by Riveline
et al. [51] in human fibroblasts and 3T3 cells that local application
of mechanical force leads to further assembly of the existing
integrin-containing molecular complex. Further, currently recog-
nized manifestations of integrin signaling are tyrosine phosphor-
ylation of specific proteins, increase in free intracellular calcium
and cAMP level and activation of MAP and Jun kinases [51].
However, as put forward by Hoffman-Kim et al. [11] it is also
possible that membrane distortion alone can reposition receptors
and ion channels and bring them in physical proximity;
consequently growth pathways could be initiated.
values were drawn as shown in a representative example in Fig. S3B. (C) Co-localization of actin filaments and phosphorylated tyrosine positions.Cyan bIII-tubulin, green actin, red phosphotyrosine. (D) Paxillin-GFP shows the same expression pattern than phosphotyrosine. Cyan bIII-tubulin,green Pax-GFP, red PY. Scale bars are 5 mm.doi:10.1371/journal.pone.0066170.g007
Table 1. Parameters for the construction of Fig. 7B.
Pillar Spacing (mm)Mean distance frompatch to pillar center (mm)
Higher border simulatedconfidence interval (mm)
Lower border simulatedconfidence interval (mm)
Density of patches onneurites (%)
0.6 0.6779 0.7765 0.6402 1766
1.2 0.8241 1.0336 0.8428 1465
2 1.0103 1.2648 1.0334 1666
3.2 1.461 1.7221 1.4285 1864
5 2.1432 2.5006 2.0404 1364
Per spacing the values for the measured mean distance of the patches to the pillar center are given, together with higher and lower border of the simulated confidenceintervals. The last column shows values for the density of patches on the neurites.doi:10.1371/journal.pone.0066170.t001
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 10 June 2013 | Volume 8 | Issue 6 | e66170
In conclusion, we show that topographic signaling can have a
major influence on neuronal polarity establishment and mainte-
nance. The first sprout, Golgi-centrosome position and axon
specification all follow the initial N-cadherin landmark on the
pillar substrate. Moreover, these events take place independently
of the pillar dimension in the range we investigated. On the other
hand, the quantitative outgrowth of neurites and more specifically
of axons is affected by pillar dimensions. Clearly, growth cone
morphology is involved in maintaining the faster outgrowth
behavior, as well as precisely positioned phosphorylated tyrosine
residues that are in tight contact with the pillars. All of these
elements eventually lead to the pillar-mediated modeling of
cytoskeletal components, such as actin and microtubules that are
important in neuronal polarity.
Figure 8. Possible model for interaction of young neurons with topography for polarization and axon formation. (A) When a neuronis located on the interface between a pillar array and a flat area (step 1) the N-cadherin patch is accumulated at the topographical contact, also F-actin is located at pillar contact via an unknown mechanism (step 2). After first sprout formation (step 3), the Golgi and centrosome are also recruitedto the interface (step 4), from which at a later time point the axon starts to form (step 5). (B) Pillar contact gives rise to growth signaling, if this isrepeated frequently enough during outgrowth of the neurite this leads to an overall growth encouragement. On the other hand if the pillars arespaced further apart, this neurite will not be able to exploit its full growth potential.doi:10.1371/journal.pone.0066170.g008
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 11 June 2013 | Volume 8 | Issue 6 | e66170
Materials and Methods
Substrate FabricationFabrication of the substrates was performed in a cleanroom
(Class 1000) environment. To create micron scale pillar structures,
first a low temperature oxide layer was deposited onto a standard 8
inch silicon wafer. After a sintering step at 455uC, standard I-line
lithography was used to define areas with diameters down to 1 mmand a minimal spacing of 600 nm. A timed reactive ion etch (RIE)
was performed to create pillars with a height of 3 mm and was
followed by a clean with the ‘piranha’ mixture (1:3 H2O2:H2SO4)
to remove the remaining photoresist. Separate substrates were
finally diced and used.
Cell Culture, Transfection, Time Lapse ImagingAnimals were handled in accordance with international (EU
Directive 86/609/EEC) and national laws governing the protec-
tion of animals used for experimental purposes, minimizing
distress during procedures. The use of animals and procedures
was approved by the Ethical Committee for Animal Welfare
(ECD, Ethische commissie Dierenwelzijn) of KULeuven and
Imec. Mouse (FVB) and rat (Wistar, Janvier) embryonic hippo-
campal neurons were prepared as described elsewhere [4] and
plated at a density of 50 000 cells per cm2 on poly-L-lysine (PLL,
P2636, Sigma-Aldrich, 0.5 mg/mL in borate buffer) coated
substrates. In general, mouse neurons were used for all quantita-
tive analyses, rat neurons were used for time lapse imaging with
the GFP-UtrCH construct. Cells were transfected in suspension
using nucleofection (Amaxa, Lonza). Neurons in the N-cadherin
and first bud analysis were kept in suspensions for 2h to allow for
regeneration of surface molecules which may have been destroyed
during trypsin treatment used for cell dissociation. Cells used for
time lapse imaging were seeded on the substrate after transfection
and imaged starting from 2 h after plating until 1 DIV under a
Zeiss Laser Scanning Microscope (LSM) 780 equipped with
custom built live imaging set-up (Oko-lab, Italy).
Immunocytochemistry and Morphological AnalysisNeurons were fixed in paraformaldehyde (4% PFA and 4%
Sucrose in PBS) at 37uC for 10 min and permeabilized for 5 min
in 0.1% Triton X-100/PBS, blocked in 2% FBS, 2% BSA, and
10% goat serum in PBS. Neurons were incubated with the
primary antibody for 1 h at room temperature or at 4uCovernight. Secondary antibodies in blocking solution were added
for 60 min, and were coupled to fluorophores Alexa-488, -568 and
-633 (Invitrogen, Life Technologies).
The following antibodies were used: anti bIII-Tubulin from
mouse (tuj-1, Covance) or rabbit (Abcam); anti-GPP130 (Cov-
ance), and anti N-cadherin (clone GC-4, Sigma-Aldrich); anti-tau-
1 (Chemicon); anti-P-Tyrosine (4G10, Upstate). Nuclei were
visualized using the Hoechst compound (Hoechst 33342, Invitro-
gen) or propidium iodide (PI, Invitrogen). N-cadherin on the
surface of neurons was detected by incubating neurons after
fixation without permeabilization with an antibody recognizing a
surface epitope of N-cadherin (clone GC-4, Sigma-Aldrich).
For the neurite outgrowth analysis, the semi-automated
Metamorph software (Molecular Devices) was applied to analyze
average and longest process length (Fig. S1). Briefly, a neurite (tuj-
1) and nuclei (PI) image were loaded into the software. Based on
this input the software performed a cell segmentation step
(‘Segmented tuj-1 image’ and ‘Segmented PI image’). The
Metamorph algorithms subsequently detected the different
parameters i.e. average and longest neurite length per cell as
plotted in Fig. 5A.
Statistical AnalysisFor the first sprout, Golgi and N-cadherin experiments,
statistical analysis of neuron populations was performed using
X2-test to determine a significance difference of the observed
distribution compared to an expected random distribution.
Growth cone areas were measured in ImageJ by default thresh-
olding of the individual images and followed by area measure-
ment. Groups were compared by Student’s t-tests.
Phosphotyrosine AnalysisAfter the acquisition of a three channel image (substrate
reflection, tuj-1 and PY) on a Zeiss LSM 780 confocal microscope,
the pillar grid was isolated with a customized script in ImageJ
(NIH, MA, USA) and the tuj-1 and PY images were thresholded
(cfr. Methods S1 and Fig. S2, B: ‘Grid image’, C: ‘Tuj-1 image’, E:
‘Segmented PY patches’). Cell bodies were excluded from this
analysis to avoid bias. Randomly positioned blobs having the same
average diameter as determined from the average of a statistical
sample of measured PY patches were randomly placed on the
thresholded tuj-1 image (Fig. S2D, ‘Simulated PY patches’).
The spatial distribution of PY patches was revealed by
calculation of the ‘nearest point to event distance’ followed by
comparison to a reference random distribution comprising the null
hypothesis H0. The method is described in greater detail elsewhere
[52]. Briefly, the mapped distribution of events (the segmented PY
image) can be recast into the conceptual framework of spatial
point processes in the plane. In the framework of hypothesis
testing, observed patterns of patches can be compared against
realizations of various types of stochastic spatial point processes
(Fig. S3A–C). A benchmark for such comparisons is the
homogeneous Poisson process in the plane because it is the
simplest and the best-studied spatial process. This process is
characterized with complete spatial randomness having the properties
of (i) homogeneity–the intensity of the process is constant over the
region of study, and (ii) spatial independence in the occurrence of
the events–numbers of the observed points in neighboring regions
do not correlate with each other.
In our approach, the locations of the patches (i.e. ‘events’) are
referenced to the immutable hexagonal grid of pillars on the
substrate (i.e. ‘observation points’, see Fig. S3A). The distribution
of nearest point to event distances is denoted conventionally by
F (r). Under CSR in the undoubted plane.
F (r)~1{ exp ({plr2), r§0, Where l~nDAD{1 ð1Þ
Here is the number of events in A, the region of interest, in this
case the tuj-1 thresholded image. However, in our measurements
we were confronted with a multitude of disjoint regions
representing the neurites’ projections (Fig. S2). In such circum-
stances, the distribution of is intractable, therefore for making
statistical inferences one needs to resort to Monte Carlo
simulations. We addressed this challenge by realizing instances
of homogeneous Poisson process bound to the regions of neurites
(patched CSR, pCSR) as described in [53]. The simulations were
performed as following: disks having the same average area as the
observed patches were randomly placed on the segmented neurite
mask (i.e. projections, Fig. S2C), the distance to the nearest point
on grid was identified and an empirical distribution was computed
for every analyzed image.
Fig. S3B shows an example for S= 2 mm of the observed data
Fr(r) that was compared to the distribution F under pCSR.
Following Diggle (1983) [52], a significance test was introduced as
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 12 June 2013 | Volume 8 | Issue 6 | e66170
described in Prodanov (2007) [53]. More detailed explanation and
equations can be found in Methods S1. Lower and upper
confidence interval boundaries were estimated from FF (r) for
every image (An example is shown in Fig. S3D). If a confidence
interval boundary is considered as a random variable then
following the Central Limit Theorem the sample average of such
variable will reflect its population value.
Finally the mean of the measured, segmented images was
compared to the 95% confidence interval boundaries that were
taken as significance levels. To obtain a statistical inference per
condition all such intervals were aggregated and averaged. The
final result for all investigated spacings is shown in Fig. 7B (lower
region in the plot is ‘attraction’ (i.e. the patches are closer to the
pillar than under CSR) while the upper region is ‘repulsion’ (i.e.
the patches are further from the pillar than under CSR).
Supporting Information
Figure S1 Workflow of morphometric analysis byMetamorph analysis and segmentation. An example of
tuj-1 and PI image of neurons at 20 h in culture on pillars of
W=1 mm, S= 1 mm used for Metamorph neurite outgrowth
analysis. In the segmentation image each cell with its neurites is
labeled by a different color.
(TIF)
Figure S2 Workflow of image processing and simula-tion steps. (A) Example of a composite confocal image with
microtubules stained in red, PY patches in green and nuclei in
blue, gray in reflectance. (B) shows the thresholded gray channel
grid, indicating the individual pillar centers. (C) The tuj-1
thresholded image where the cell bodies are cut out. (D) The
simulated PY patches shown in cyan on the tuj-1 image and (E)the segmented PY patches. (F) The histogram of patch areas for
this particular example, the mean patch size is 0.33160.002 mm2
(mean 6 sem).
(TIF)
Figure S3 Workflow of the Monte Carlo statisticalanalysis. (A) On the schematic the outline of the neurites is
shown in black, the pillar centers are shown in gray, simulated
patches in cyan and observed PY patches in dark blue. (B) Detail
of schematic shown in (A). With a nearest neighbor algorithm the
closest patch-to-pillar distances were computed for both the
simulated and observed patches (r1s vs r2s for the simulated and r1rvs r2r for the observed patches). (C) The pillar centers are ‘points’
and the patches (observed or simulated, indicated by a star) are
‘events’. The nearest point to event was determined as min (r1,r2)for both simulated and measured patches. (D) An example for
W=1.6 mm and S= 2 mm of the cumulative distribution functions
(cdf) used for constructing Fig. 7B. At the 50% level of the cdf, the
corresponding distances for the observed data, lower and upper
confidence interval were eventually plotted on the y-axis of Fig. 7B
vs the spacing for which the analysis was performed.
(TIF)
Table S1 Detailed data of the individual analyzedimages. Per spacing at least 11 images were analyzed, the real
and simulated mean distances to the pillar center are given per
image as well as the calculated p-values.
(DOCX)
Methods S1 Supplementary Methods.
(DOCX)
Movie S1 Behavior of neurites on a pillar bed. Hippo-
campal neuron (GFP-UtrCH) at 1 DIV growing on pillar
substrate. Full time lapse of fragment shown in Fig. 5D. White
arrows indicate actin patches enriched at pillar contacts. Green
arrow position shows the minor neurite extending filopodia to the
pillars when extending. 90 s per frame. W=2.8 mm, S=1.6 mm at
the left side of the ridge, W=2.8 mm, S= 1.8 mm at the right side.
Scale bar is 10 mm.
(AVI)
Acknowledgments
The authors thank Mrs. K. Van Keer and Dr. O. Krylychkina for the
culturing of primary hippocampal neurons, Dr. D. R. Rand for SEM
image acquisition.
Author Contributions
Conceived and designed the experiments: LM AG DB CGD. Performed
the experiments: LM. Analyzed the data: LM DP AG. Contributed
reagents/materials/analysis tools: LM AG DP DB CGD CB. Wrote the
paper: LM AG DP DB CGD CB.
References
1. Arimura N, Kaibuchi K (2007) Neuronal polarity: from extracellular signals to
intracellular mechanisms. Nat Rev Neurosci 8: 194–205.
2. de Anda FC, Gaertner A, Tsai LH, Dotti CG (2008) Pyramidal neuron polarity
axis is defined at the bipolar stage. J Cell Sci 121: 178–185.
3. Dotti CG, Sullivan CA, Banker GA (1988) The establishment of polarity by
hippocampal neurons in culture. J Neurosci 8: 1454–1468.
4. Goslin K, Banker G (1989) Experimental observations on the development of
polarity by hippocampal neurons in culture. J Cell Biol 108: 1507–1516.
5. Gaertner A, Fornasiero EF, Munck S, Vennekens K, Seuntjens E, et al. (2012)
N-cadherin specifies first asymmetry in developing neurons. EMBO J 31: 1893–
1903.
6. Pollarolo G, Schulz JG, Munck S, Dotti CG (2011) Cytokinesis remnants define
first neuronal asymmetry in vivo. Nat Neurosci 14: 1525–1533.
7. de Anda FC, Pollarolo G, Silva JSD, Camoletto PG, Feiguin F, et al. (2005)
Centrosome localization determines neuronal polarity. Nature 436: 704–708.
8. Dowell-Mesfin NM, Abdul-Karim MA, Turner AMP, Schanz S, Craighead
HG, et al. (2004) Topographically modified surfaces affect orientation and
growth of hippocampal neurons. J Neural Eng 1: 78–90.
9. Esch T, Lemmon V, Banker G (1999) Local presentation of substrate molecules
directs axon specification by cultured hippocampal neurons. J Neurosci 19:
6417–6426.
10. Fozdar DY, Lee JY, Schmidt CE, Chen S (2010) Hippocampal neurons respond
uniquely to topographies of various sizes and shapes. Biofabrication 2: 035005.
11. Hoffman-Kim D, Mitchel JA, Bellamkonda RV (2010) Topography, cell
response, and nerve regeneration. Annu Rev Biomed Eng 12: 203–231.
12. Barnes AP, Solecki D, Polleux F (2008) New insights into the molecular
mechanisms specifying neuronal polarity in vivo. Curr Opin Neurobiol 18: 44–
52.
13. Bruder JM, Lee AP, Hoffman-Kim D (2007) Biomimetic materials replicating
schwann cell topography enhance neuronal adhesion and neurite alignment
in vitro. J Biomater Sci Polym Ed 18: 967–982.
14. Halfter W, Deiss S, Schwarz U (1985) The formation of the axonal pattern in the
embryonic avian retina. J Comp Neurol 232: 466–480.
15. Hynes RO, Patel R, Miller RH (1986) Migration of neuroblasts along
preexisting axonal tracts during prenatal cerebellar development. J Neurosci 6:
867–876.
16. Fozdar DY, Lee JY, Schmidt CE, Chen S (2011) Selective axonal growth of
embryonic hippocampal neurons according to topographic features of various
sizes and shapes. Int J Nanomedicine 6: 45–57.
17. Gomez N, Lu Y, Chen S, Schmidt CE (2007) Immobilized nerve growth factor
and microtopography have distinct effects on polarization versus axon
elongation in hippocampal cells in culture. Biomaterials 28: 271–284.
18. Moore SW, Sheetz MP (2011) Biophysics of substrate interaction: influence on
neural motility, differentiation, and repair. Dev Neurobiol 71: 1090–1101.
19. Rajnicek A, Britland S, McCaig C (1997) Contact guidance of cns neurites on
grooved quartz: influence of groove dimensions, neuronal age and cell type.
J Cell Sci 110 (Pt 23): 2905–2913.
20. Hanson JN, Motala MJ, Heien ML, Gillette M, Sweedler J, et al. (2009)
Textural guidance cues for controlling process outgrowth of mammalian
neurons. Lab Chip 9: 122–131.
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 13 June 2013 | Volume 8 | Issue 6 | e66170
21. Ferrari A, Cecchini M, Serresi M, Faraci P, Pisignano D, et al. (2010) Neuronal
polarity selection by topography-induced focal adhesion control. Biomaterials31: 4682–4694.
22. Migliorini E, Grenci G, Ban J, Pozzato A, Tormen M, et al. (2011) Acceleration
of neuronal precursors differentiation induced by substrate nanotopography.Biotechnol Bioeng 108: 2736–2746.
23. Whitington PM, Quilkey C, Sink H (2004) Necessity and redundancy ofguidepost cells in the embryonic drosophila cns. Int J Dev Neurosci 22: 157–163.
24. O’Connor T (1999) Intermediate targets and segmental pathfinding. Cellular
and molecular life sciences 55: 1358–1364.25. Burkel BM, von Dassow G, Bement WM (2007) Versatile fluorescent probes for
actin filaments based on the actin-binding domain of utrophin. Cell MotilCytoskeleton 64: 822–832.
26. Gaertner A, Dotti CG (2011) Actin and neuronal polarity. In: Gallo G, LanierLM, editors, Neurobiology of Actin, Springer New York, volume 5 of Advances in
Neurobiology. 161–176. http://dx.doi.org/10.1007/978-1-4419-7368-9_9.
10.1007/978–1-4419–7368–9_9.27. Solecki DJ, Trivedi N, Govek EE, Kerekes RA, Gleason SS, et al. (2009) Myosin
ii motors and f-actin dynamics drive the coordinated movement of thecentrosome and soma during cns glial-guided neuronal migration. Neuron 63:
63–80.
28. Zmuda JF, Rivas RJ (1998) The golgi apparatus and the centrosome arelocalized to the sites of newly emerging axons in cerebellar granule neurons
in vitro. Cell Motil Cytoskeleton 41: 18–38.29. de Anda FC, Tsai LH (2011) Axon selection: From a polarized cytoplasm to a
migrating neuron. Commun Integr Biol 4: 304–307.30. Higginbotham HR, Gleeson JG (2007) The centrosome in neuronal develop-
ment. Trends Neurosci 30: 276–283.
31. Clark P, Britland S, Connolly P (1993) Growth cone guidance and neuronmorphology on micropatterned laminin surfaces. J Cell Sci 105 (Pt 1): 203–212.
32. Jang KJ, Kim MS, Feltrin D, Jeon NL, Suh KY, et al. (2010) Two distinctfilopodia populations at the growth cone allow to sense nanotopographical
extracellular matrix cues to guide neurite outgrowth. PLoS ONE 5: e15966–.
33. Chacon MR, Navarro AI, Cuesto G, del Pino I, Scott R, et al. (2012) Focaladhesion kinase regulates actin nucleation and neuronal filopodia formation
during axonal growth. Development 139: 3200–3210.34. Robles E, Gomez TM (2006) Focal adhesion kinase signaling at sites of integrin-
mediated adhesion controls axon pathfinding. Nat Neurosci 9: 1274–1283.35. Webb DJ, Donais K, Whitmore LA, Thomas SM, Turner CE, et al. (2004) Fak-
src signalling through paxillin, erk and mlck regulates adhesion disassembly. Nat
Cell Biol 6: 154–161.36. Pasapera AM, Schneider IC, Rericha E, Schlaepfer DD, Waterman CM (2010)
Myosin ii activity regulates vinculin recruitment to focal adhesions through fak-mediated paxillin phosphorylation. J Cell Biol 188: 877–890.
37. Seo CH, Furukawa K, Montagne K, Jeong H, Ushida T (2011) The effect of
substrate microtopography on focal adhesion maturation and actin organizationvia the rhoa/rock pathway. Biomaterials 32: 9568–9575.
38. Sero JE, Thodeti CK, Mammoto A, Bakal C, Thomas S, et al. (2011) Paxillin
mediates sensing of physical cues and regulates directional cell motility by
controlling lamellipodia positioning. PLoS One 6: e28303.
39. Lamoureux P, Ruthel G, Buxbaum RE, Heidemann SR (2002) Mechanical
tension can specify axonal fate in hippocampal neurons. J Cell Biol 159: 499–
508.
40. Cheng PL, Poo MM (2012) Early events in axon/dendrite polarization. Annu
Rev Neurosci 35: 181–201.
41. Roth S, Bisbal M, Brocard J, Bugnicourt G, Saoudi Y, et al. (2012) How
morphological constraints affect axonal polarity in mouse neurons. PLoS One 7:
e33623.
42. Ganz A, Lambert M, Saez A, Silberzan P, Buguin A, et al. (2006) Traction
forces exerted through n-cadherin contacts. Biol Cell 98: 721–730.
43. Frey MT, Tsai IY, Russell TP, Hanks SK, Wang YL (2006) Cellular responses to
substrate topography: role of myosin ii and focal adhesion kinase. Biophys J 90:
3774–3782.
44. Balaban NQ, Schwarz US, Riveline D, Goichberg P, Tzur G, et al. (2001) Force
and focal adhesion assembly: a close relationship studied using elastic
micropatterned substrates. Nat Cell Biol 3: 466–472.
45. Kim DH, Han K, Gupta K, Kwon KW, Suh KY, et al. (2009)
Mechanosensitivity of fibroblast cell shape and movement to anisotropic
substratum topography gradients. Biomaterials 30: 5433–5444.
46. Matschegewski C, Staehlke S, Loeffler R, Lange R, Chai F, et al. (2010) Cell
architecture–cell function dependencies on titanium arrays with regular
geometry. Biomaterials 31: 5729–5740.
47. Braeken D, Huys R, Loo J, Bartic C, Borghs G, et al. (2010) Localized electrical
stimulation of in vitro neurons using an array of sub-cellular sized electrodes.
Biosens Bioelectron.
48. Huys R, Braeken D, Jans D, Stassen A, Collaert N, et al. (2012) Single-cell
recording and stimulation with a 16k micro-nail electrode array integrated on a
0.18 um cmos chip. Lab Chip 12: 1274–1280.
49. Mitra SK, Hanson DA, Schlaepfer DD (2005) Focal adhesion kinase: in
command and control of cell motility. Nat Rev Mol Cell Biol 6: 56–68.
50. Makino A, Prossnitz ER, Bunemann M, Wang JM, Yao W, et al. (2006) G
protein-coupled receptors serve as mechanosensors for fluid shear stress in
neutrophils. American Journal of Physiology-Cell Physiology 290: C1633–
C1639.
51. Riveline D, Zamir E, Balaban NQ, Schwarz US, Ishizaki T, et al. (2001) Focal
contacts as mechanosensors: externally applied local mechanical force induces
growth of focal contacts by an mdia1-dependent and rock-independent
mechanism. J Cell Biol 153: 1175–1186.
52. Diggle P (1983) Statistical analysis of spatial point patterns. london: Academic
press. : 148 p.
53. Prodanov D, Nagelkerke N, Marani E (2007) Spatial clustering analysis in
neuroanatomy: applications of different approaches to motor nerve fiber
distribution. J Neurosci Methods 160: 93–108.
Neuronal Polarization and Growth by Topography
PLOS ONE | www.plosone.org 14 June 2013 | Volume 8 | Issue 6 | e66170